MSc in Computing - Major 2: Data Analytics
Postgraduate Prospectus - MSc in Computing (with Major Options)
In today's increasingly data-driven world, the demand for professionals with expertise in data analytics has been steadily rising. This course is designed to equip students with the knowledge and skills necessary to excel in this field.
Overview
As big data continues to play a crucial role in various industries, organisations are seeking individuals who can effectively gather, manage, and analyse large quantities of data to drive informed decision-making and gain a competitive edge.
This programme equips students with a comprehensive knowledge of the challenges, methodologies, and resources necessary to analyse substantial volumes of raw data effectively and derive insightful conclusions from it.
During this programme, you’ll explore the fundamentals of Data Analytics. You’ll also study topics including Machine Learning, Cloud Technologies, Computational Science, Data Management and Visualisation, and more. During the summer, you will complete a project practicum where you will develop a prototype software system related to data analytics that targets a real-world problem. Whether you're analysing processes, proposing innovative solutions, or collaborating within a team, this practical experience empowers you to excel in your field and make a tangible impact.
Unlock the power of data
Data analytics has enabled predictive modelling for disease outbreaks, streaming platforms use it to recommend content based on user preferences, and it is even used in fraud detection. The opportunities in this area are endless and skilled personnel are in high-demand in a variety of sectors, from non-government organisations to aerospace. As a graduate of this course, you'll be equipped to tackle real-world data challenges with confidence, enabling you to add value to your organisation and take your career to the next level.
Programme Structure
This flexible course allows students to study part-time or full-time on our DCU Glasnevin campus. The McNulty building is home to the School of Computing and students get an opportunity to study in a modern, state of the art building with excellent teaching, laboratory, workshop and computing facilities.
Part-time students will have six hours of lectures and labs a week, which will take place after 4pm. Full-time students will have roughly 12 hours. Added to this will be all of the directed laboratory and study work required to complete continual assessments.
Students will undertake modules in the following areas:
- Professional & Research Practice
- Statistical Data Analysis
- Data Management and Visualisation
- Cloud Technologies
- Artificial Intelligence (Info & Info Seeking)
- Mathematical Methods/Computational Science
- Data Analytics and Data Mining
- Machine Learning
- Practicum (Data Analytics)
This Major is available both Full Time and Part Time.